International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

A Study on Identifying and Categorising Students based on Personal Learning Traits for Adaptive Learning Systems

Author : Aryaman M ¹ T. Anoop Sai ² Dr. Sandhya N ³

Date of Publication :6th September 2022

Abstract: Sending messages automatically without the involvement of human input is known as Message Automation or Text Automation. This study aims to identify and Categorise students based on Personal Learning Traits for Adaptive Learning Systems.Despite the growing academic research in the field of adaptive learning, its various applications and implementations, the field lacks a comprehensive literary analysis that categorises users of adaptive learning apparatuses depending on independent understanding abilities in these settings. This study provides an overview of various student personality attributes and methods for grouping them together to provide better and improve adaptive learning environments and systems to cater to a larger user base.

Reference :

1. Peter Brusilovsky (2003). "Adaptive and Intelligent Web-based Educational Systems". International Journal of Artificial Intelligence in Education. 13 (2–4): 159–172.
2. Andrie, A. M. (2011). Positive And Negative Emotions Within The Organizational Context. Global Journal of Human Social Science, 11(9), 26–39.
3. Forehand, M. (2010). Bloom’s Taxonomy. Emerging Perspectives on Learning, Teaching and Technology Bloom’s (Vol. 41).
4. Santos, O. C., Boticario, J. G., & Pérez-Marín, D. (2014). Extending web-based educational systems with personalised support through User Centred Designed recommendations along the e-learning life cycle. Science of Computer Programming, 88, 92–109.
5. Shute, V., & Towle, B. (2003). Adaptive E-Learning. Educational Psychologist, 38(2), 105–114.
6. Truong, H. (2015). Doctoral Consortium: Integrating Learning Styles into adaptive e-learning system., 645–647
7. Forehand, M. (2010). Bloom’s Taxonomy. Emerging Perspectives on Learning, Teaching and Technology Bloom’s (Vol. 41). Retrieved from
8. Vandewaetere, M., Desmet, P., & Clarebout, G. (2011). The contribution of learner characteristics in the development of computer-based adaptive learning environments. Computers in Human Behaviour, 27(1), 118– 130.
9. Identification of personal traits in adaptive learning environment: Systematic literature review Nur Baiti Afini Normadhi, Liyana Shuib, Hairul Nizam Md Nasir, Andrew Bimba, Norisma Idris, Vimala Balakrishnan.